Assessing the impact of substance use treatment for preventing criminal justice system contact in Chile

M. Mateo Piñones1, 2, , A. González-Santa Cruz1, 3, , A. Castillo-Carniglia4, 5,


1 Young Researcher, Millennium Nucleus for the evaluation and analysis of Drug Policies
2 Ph.D. student, School of Public Health, Universidad de Chile
3 Ph.D. student, Griffith University, Australia
4 Director , Millennium Nucleus for the evaluation and analysis of Drug Policies
5 Associate Professor, Society & Health Research Center

Background

Research has shown that reducing SUDs through effective treatment leads to a reduction in criminal activity\(^{[1]}\). However, most evidence comes from developed countries, and results from the Latin American context are largely unknown\(^{[2]}\). The social, cultural, economic, epidemiological context and substance use treatment (SUT) policy response are different in this region, making the question about SUT effectiveness through locally based data relevant\(^{[3]}\). We analyzed Chile as a case study and examined the impact of SUT on the prevention of contact with the criminal justice system (CJS) in the middle (3 years) and long term (5 years).

Methods

  • Design: a population-based record-linkage retrospective cohort design.
  • Participants: patients enrolled in publicly funded SUT programs in Chile, 2010-2019.
  • Exposure: Treatment completion, Late (>= 3months of treatment) & Early dropout (<3 months); Outcome: contact with the CJS (offenses ending with a condemnatory sentence and offenses that ended with imprisonment after baseline treatment outcome)
Analysis plan
  • We calculated cumulative incidence rates and incidence rate ratios(IRR)
  • We used Royston-Parmar survival models and adjust for the effects of other factors, and predicted standardized survival probabilities and restricted mean survival times (RMST)\(^{[4]}\).
  • We imputed missing data under MAR assumption\(^{[5]}\).
  • We calculated e-values of the strength of confounding needed to take away the associations between treatment outcome and contact with CJS
  • Codes are available at https://fondecytacc.github.io/nDP/index_prop_grant22_23.html. Covariates are listed below:
  • Treatment setting
  • Sex
  • Substance use onset age
  • Educational attainment
  • Primary substance at admission
  • Primary substance at admission usage frequency
  • Occupational status
  • Poly-substance use
  • Number of children (binary)
  • Tenure status of households
  • Macrozone
  • Number of previous offenses (violent)
  • Number of previous offenses (acquisitive)
  • Number of previous offenses (substance-related)
  • Number of previous offenses (other)
  • Psychiatric comorbidity (ICD-10)
  • Substance use severity (dependence status) (ICD-10)
  • Urban/rural municipality of residence
  • Percentage of poverty of the municipality of residence
  • Initial substance
  • Birth year
  • Cohabitation status
  • Physical comorbidity
  • Admission Age
  • Preliminary Results

    Of the 109,756(patients= 85,048) SENDA records of admissions, 70,863(83%) were eligible to be matched with the Prossecutor’s Office database (discarded ongoing treatments or treatments that ended in referrals).
  • Condemnatory sentence. 22,287(31%).
  • Imprisonment. 5,144(7%).
    • Early dropout vs. Treatment completion: Patients completing treatment took longer to an offense leading to condemnatory sentence (IRR= 2.18 95% CI 2.09,2.27; aHR[adjusted hazard ratio]: 1.74 95%CI 1.66, 1.83) condemnatory sentence and imprisonment (IRR= 2.90 95% CI 2.64,3.18; aHR= 1.99 95%CI 1.79, 2.22).
    • Late dropout vs. Treatment completion: Patients completing treatment took longer to condemnatory sentence (IRR= 1.73 95% CI 1.67,1.80; aHR=1.58 95%CI 1.52, 1.65) and to imprisonment (IRR= 1.93 95% CI 1.77,2.10; aHR=1.65 95%CI 1.51, 1.81).
    • Late vs. Early dropout: Patients completing treatment took longer to condemnatory sentence (IRR= 1.26 95% CI 1.22,1.30) and imprisonment (IRR= 1.50 95% CI 1.41,1.61).
    E-values
  • Condemnatory Sentence: E-value of at least 2.19 for Early and 2.01 for Late dropout vs. treatment completion at baseline (t=0).
  • Imprisonment: E-value of at least 2.99 for Early and 2.38 for Late dropout vs. treatment completion at baseline (t=0).
  • The following figure depicts the predicted differences in survival probabilities and RMTLs for committing an offense that results in a condemnatory sentence and imprisonment.
    Differences in survival probabilities(left) and RMSTs(right) for time-to-condemnatory sentence(up) & imprisonment(bottom)

    Figure 1: Differences in survival probabilities(left) and RMSTs(right) for time-to-condemnatory sentence(up) & imprisonment(bottom)

    Discussion

    • SUT can be effective in preventing contact with the criminal justice system (CJS) in Chile.
    • More research is needed to understand the effects of SUT on contact with the CJS.
    • Completing SUT can help to reduce the harms of substance use disorders and criminality.

    References

    [1] M. Prendergast, D. Podus, E. Chang, et al. “Erratum to The effectiveness of drug abuse treatment: a meta-analysis of comparison group studies”. In: Drug and Alcohol Dependence - DRUG ALCOHOL DEPENDENCE 84 (sept.. 2006), pp. 133-133. DOI: 10.1016/j.drugalcdep.2006.02.002.

    [2] H. Klingemann. “Successes and Failures in Treatment of Substance Abuse: Treatment System Perspectives and Lessons from the European Continent”. In: Nordisk Alkohol- and Narkotikatidskrift 37.4 (2020), pp. 323-37.

    [3] M. Mateo Pinones, A. González-Santa Cruz, R. Portilla Huidobro, et al. “Evidence-based policymaking: Lessons from the Chilean Substance Use Treatment Policy”. En. In: Int. J. Drug Policy 109.103860 (nov.. 2022), p. 103860.

    [4] P. Lambert. STPM2: Stata module to estimate flexible parametric survival models. Statistical Software Components, Boston College Department of Economics. feb.. 2010. URL: https://ideas.repec.org/c/boc/bocode/s457128.html.

    [5] M. Mayer. “missRanger: Fast Imputation of Missing Values”. (2023). R package version 2.2.0. URL: https://github.com/mayer79/missRanger.

    Funding sources

    • This work was funded by ANID - Millennium Science Initiative Program - N° NCS2021_003 (Castillo-Carniglia) and N° NCS2021_013 (Calvo); Authors have no conflict of interest to declare